Me, myself and iRobot

Pooja Viswanathan

Outline

• My research : The Intelligent Wheelchair

• Other robots

• Discussion

Learning Goals

• explain how technology can be used at home and in healthcare (give examples of some robots discussed in class)

• distinguish between autonomous and semi-autonomous systems, along with strengths of weaknesses of each.

• discuss the challenges in the field of assistive technology

• discuss Asimov's laws

The Aging Population

• Proportion of older adults in the population continues to grow

• Of the 1.5 million people residing in nursing homes, 60-80% have been diagnosed with dementia, primarily Alzheimer’s disease (Payne et al., 2002)

• Older adults with cognitive impairments not allowed to operate powered wheelchairs

• Prohibition of powered wheelchair use and the lack of strength required to use manual wheelchairs effectively reduce mobility -> social isolation, depression and increased dependence on caregivers

Assistive Technology

• Several technologies exclude people with disabilities• Wikipedia: “Assistive Technology (AT) is a generic term

that includes assistive, adaptive, and rehabilitative devices and the process used in selecting, locating, and using them. AT promotes greater independence for people with disabilities by enabling them to perform tasks that they were formerly unable to accomplish, or had great difficulty accomplishing, by providing enhancements to or changed methods of interacting with the technology needed to accomplish such tasks.”

My project

• Ensures safety

• Provides assistance in navigation

Intelligent powered wheelchair for older adults with cognitive impairment that:

Safety

• 73-80% of older adults fall or trip after being hit by wheelchair (Corfman, 2001)

• Even minor collision could startle elderly residents and lead to fall

• 5-10% of falls could result in fracture (Nevitt, 1989)

• 40% of older adults who sustain a hip fracture die within 6 months due to complications (Jaglal et al., 1996)

• Need non-contact anti-collision system!!

System overview

System Overview

Control Strategy

Semi-Autonomous

ManualAutonomous

Strength:

No need for user input

Weakness:

User might want some control

Strength:

User has full control

Weakness: Tedious, user might not have ability

Combines strengths of other 2 systems

How do we determine who has control and when?

Collision Avoidance

• Find the distance to objects – stored in depth maps

• Use this to create a map of all obstacles in front of the wheelchair – occupancy map

Depth• Stereopsis

Left Image

Right Image Depth Map

Point Grey’s Bumblebee Camera

Occupancy Grid

Depth Map 2D Projection - Occupancy Map

Example OGs

Example OGs

Example OGs

Example OGs

Example OGs

Example OGs

Example OGs

Collision Avoidance

• If object detected within a specified distance threshold, wheelchair is stopped

• Compute direction around obstacle with greatest amount of free space

Collision Avoidance

Prompt: “Try turning left”

Most free space is to the

left of the object

Demo!!!

Pilot Study

• Experiments conducted to test efficacy of anti-collision and prompting system

• Conducted within controlled environment

Pilot Study

• Trials tested:

– Detection of objects commonly found in LTC facility

– Collision avoidance

– Correct prompt issued

Object Detection

• Anti-collision system was tested with the following commonly-found objects:– A painted white wall with a flat finish– A light green aluminum 4-wheeled walker– A silver aluminum walking cane– A person who was standing still– A person who was moving

Results

• Misses occurred during wall and cane conditions

• System performs better on larger and more textured objects

Overall Anti-collision Results

Results

Distance between wheelchair and object when stopped

Results

Overall Prompting Results

Now what???

• Example Scenario: I’m hungry…

It’s 11:50 a.m. Mary

eats lunch at 12:00

Now what???

• Example Scenario: I’m hungry…

It’s lunch time! Let’s go to the

dining hall!

Navigation Assistance

• To assist in navigation, wheelchair must know three things:

– Where the user wants to go (destination)– Where the chair is located– Where the destination is located

• User destination - learned from past behaviours and/or user schedules

• Locations – need maps!!

Automated Map Building

• Wheelchair automatically builds map of environment using visual landmarks

• Wheelchair can then find its current location by matching landmarks in the incoming images with those in the map

• Label popular destinations (e.g. kitchen, lounge, etc.) on map

Planning and Prompting

• Remind the user of where he/she needs to be

• Plan the shortest (?) path to the destination

• Prompt the user as necessary (audio, visual, haptic)

• Avoid obstacles on the way

The Big Picture

Future Work

• Wheelchair prompts “Go to dining hall” when user really wants to go somewhere else – query the user?

• Level of prompting – adjusted for each user based on errors made, severity of impairment, past responsiveness to prompts, etc.

Other ATs

• COACH

Issues

• Ethics

• Liability

• Privacy

• ??

Robots

• Examples??

Robots

• Roomba

• WiiBot• Kismet

Discussion

• Should robots look/act human?– Japanese Humanoid– Canadian Fembot

Discussion

• Should robots look/act human?

• What about army robots?– Shooting robot

Discussion

• Should robots look/act human?

• What about army robots?

• When/how should we use robots?

Asimov’s Laws:Three Laws of Robotics

• A robot may not harm or injure a human being.

• A robot must obey the orders that a human being gives to it, unless it would result in injury.

• A robot must protect its own existence as long as it does not interfere with laws number one or two.